The invention relates to a method and apparatus for suppressing audible noise in speech transmission by means of a multi-layer self-organizing fed-back neural network.
In telecommunications and in speech recording in portable recording equipment, a problem is that the intelligibility of the transmitted or recorded speech may be impaired greatly by audible noise. This problem is especially evident where car drivers telephone inside their vehicle with the aid of hands-free equipment. In order to suppress audible noise, it is common practice to insert filters into the signal path. In this respect, the utility of classical bandpass filters is limited as the audible noise is most likely to appear with in the same frequency ranges as the speech signal itself. For this reason, adaptive filters are needed which automatically adapt to existing noise and to the properties of the speech signal to be transmitted. A number of different concepts is known and used to this end.
A device derived from optimum matched filter theory is the Wiener-Kolmogorov Filter (S. V. Vaseghi, Advanced Signal Processing and Digital Noise Reductionxe2x80x9d, John Wiley and Teubner-Verlag, 1996). This method is based on minimizing the mean square error between the actual and the expected speech signals. This filtering concept calls for a considerable amount of computation. Besides, a theoretical requirement of this and most other prior methods is that the audible noise signal be stationary.
The Kalman filter is based on a similar filtering principle (E. Wan and A. Nelson, Removal of noise from speech using the Dual Extended Kalman Filter algorithm, Proceedings of the IEEE International Conference on Acoustics and Signal Processing (ICASSP""98), Seattle 1998). A shortcoming of this filtering principle is the extended training time necessary to determine the filter parameter.
Another filtering concept has been known by H. Hermansky and N. Morgan, RASTA processing of speech, IEEE Transactions on Speech and Audio Processing, Vol. 2, No. 4, p. 587, 1994. This method also calls for a training procedure; besides, different kinds of noise call for different parameter settings.
A method known as LPC requires lengthy computation to derive correlation matrices for the computation of filter coefficients with the aid of a linear prediction process; in this respect, see T. Arai, H. Hermansky, M. Paveland, C. Avendano, Intelligibility of Speech with Filtered Time Trajectories of LPC Cepstrum, The Journal of the Acoustical Society of Maerica, Vol. 100, No. 4, Pt. 2, p. 2756, 1996.
Other prior methods use multi-layer perceptron type neural networks for speech amplification as described in H. Hermansky, E. Wan, C. Avendano, Speech Enhancement Based on Temporal Processing. Proceedings of the IEEE International Conference on Acoustics and Signal Processing (ICASSP""95), Detroit, 1995.
The object of the present invention is to provide a method in which a moderate computational effort is sufficient to identify a speech signal by its time and spectral properties and to remove audible noise from it.
This object is achieved by a filtering function F(f,T) for noise filtering which is defined by a minima detection layer, a reaction layer, a diffusion layer and an integration layer.
A network organized this way recognizes a speech signal by its time and spectral properties and can remove audible noise from it. The computational effort required is low, compared with prior methods. The method features a very short adaptation,time within which the system adapts to the nature of the noise. The signal delay involved in signal processing is very short so that the filter can be used in real-time telecommunications.
Further scope of applicability of the present invention will become apparent from the detailed description given hereinafter. However, it should be understood that the detailed description and specific examples, while indicating preferred embodiments of the invention, are given by way of illustration only, since various changes and modifications within the spirit and scope of the invention will become apparent to those skilled in the art from this detailed description.